A small practice, deliberately so.
Summit Epi Analytics is the independent consulting practice of Dr. Nicole Bohme Carnegie — a biostatistician and epidemiologist specializing in causal inference for interconnected populations, spanning infectious disease transmission, cluster-randomized trials, and network-aware behavioral interventions. The practice runs at part-time capacity, by design, so the work stays bounded, the answers stay honest, and the relationships stay personal.
Nicole Bohme Carnegie, PhD
Founder & Principal · Colorado Springs, CO
Nicole's career spans academia, biotech, and applied public health. She has led teams developing outbreak forecasting and early-warning systems used by public health agencies and industry partners; held a $2M NIH R01 as PI on network-informed HIV prevention trial design; and built mechanistic, agent-based, and compartmental models in industry at Ginkgo Biosecurity and The Public Health Company.
Her methodological work focuses on causal inference under interference and social processes — when one unit's treatment affects another's outcome, which is the rule rather than the exception in infectious disease. She is the original author of the CRAN package treatSens for sensitivity to unmeasured confounding, has three Atlantic Causal Inference Conference data-analysis competition wins, and has delivered an FDA-contracted Targeted Learning webinar on causal inference with BART.
Operationally, she has worked with the Rwanda Biomedical Centre on the Kigali International Airport surveillance study (IJID Regions, 2025), with the WHO Immunization programme (2005, 2011), with the Harvard / De Gruttola group on HIV genetic linkage in Botswana, and with Statistics Without Borders on UNICEF engagements.
Selected credentials
- PhD, Statistics
- NIH R01 Principal Investigator
- CRAN package author · treatSens
- 3× ACIC data-analysis competition winner
- FDA Targeted Learning webinar lecturer
- Co-author, Rwanda Biomedical Centre · IJID Regions 2025
- Former Senior Epidemiologist · Ginkgo Biosecurity
- Statistics Without Borders · UNICEF engagements
The intersection is the point.
Most causal inference experts don't do infectious disease and scenario modeling. Most infectious disease modelers don't do rigorous causal inference. Summit Epi Analytics sits at that intersection on purpose. Ignoring interference skews our understanding of the risk of the population; models that ignore causal identifiability mislead the decisions they were meant to inform. The combination is the work.
Bounded by design.
Summit Epi Analytics runs at part-time capacity — never more than two active engagements plus one in scoping. Travel as needed, but not more than 10% of the year and with at least 2 weeks notice. Remote-first by default. The constraints are not limitations; they are how the practice keeps its promises.